Analysis of Diagnostic Efficacy of the International Ovarian Tumor Analysis ADNEX Model and the ACR O-RADS US (Ovarian-Adnexal Reporting and Data System) for Benign and Malignant Ovarian Tumors: A Retrospective Study in a Tumor Center in Northeast China.

This study is to analyze and compare the diagnostic efficacy of the ADNEX model and O-RADS in Northeast China for benign and malignant ovarian-adnexal tumors. From July 2020 to February 2022, ultrasound images of 312 ovarian-adnexal masses included in the study were analyzed retrospectively, and the properties of these masses were identified using the ADNEX model and O-RADS. The diagnostic efficiency of the ADNEX model and O-RADS was analyzed using a ROC curve, and the capacities of the two models in differentiating benign and malignant ovarian masses at the optimum cutoff value were compared, as well as the consistency of their diagnosis results was evaluated. The study included 312 ovarian-adnexal masses, including 145 malignant masses and 167 benign masses from 287 patients with an average age of (46.8 ± 11.3) years. The AUC of the ADNEX model was 0.974, and the optimum cutoff value was the risk value > 24.2%, with the corresponding sensitivity and specificity being 97.93 and 86.83, respectively. The AUC of the O-RADS was 0.956, and the optimum cutoff value was > O-RADS 3, with the corresponding sensitivity and specificity being 97.24 and 85.03, respectively. The AUCs of the two models were 0.924 and 0.911 at the optimum cutoff values, with no statistical differences between them (P = 0.284). Consistency analysis: the kappa values of the two models for the determination and pathological results of masses were 0.840 and 0.815, respectively, and that for the diagnostic outcomes was 0.910. Both the ADNEX model and O-RADS had good diagnostic performance in people from Northeast China. Their diagnostic capabilities were similar, and diagnostic results were highly consistent at the optimum cutoff values.

Recent advances in palladium-catalyzed sulfonylation via SO2 insertion.

The importance of sulfonyl-group-containing compounds, such as sulfonamides, sulfones, sulfinate esters, and sulfonyl fluorides, in pharmaceuticals, bioactive molecules, and natural products cannot be overstated. The new development of palladium-catalyzed sulfonylation via SO2 insertion represents a crucial advancement in organic synthesis, enabling the direct α,α-difunctionalization of SO2 and providing efficient access to an array of structure-diverse sulfonyl-containing compounds. Although there have been numerous reviews about SO2 insertion, many of them only cover specific aspects of palladium-catalyzed reactions, leading to an oversight of some important works. Besides, these reviews often lack detailed discussions and systematic conclusion on reaction mechanisms, and fail to comprehensively summarize the significant research achievements in palladium-catalyzed reactions over the past few years. Herein, we aim to systematically consolidate the recent advances in palladium-catalyzed sulfonylation via SO2 insertion, elucidate the underlying reaction mechanism, and highlight some unsolved challenges in this segment. This review seeks to serve as a valuable resource for researchers, assisting in the continued development of palladium-catalyzed sulfonylation methodologies.

Safety and efficacy of baricitinib in steroid-resistant or relapsed immune thrombocytopenia: An open-label pilot study.

Patients with steroid-resistant or relapsed immune thrombocytopenia (ITP) suffer increased bleeding risk and impaired quality of life. Baricitinib, an oral Janus-associated kinases (JAK) inhibitor, could alleviate both innate and adaptive immune disorders without inducing thrombocytopenia in several autoimmune diseases. Accordingly, an open-label, single-arm, phase 2 trial (NCT05446831) was initiated to explore the safety and efficacy of baricitinib in ITP. Eligible patients were adults with primary ITP who were refractory to corticosteroids and at least one subsequent treatment, and had platelet counts below 30 × 109/L at enrolment. Participants received baricitinib 4 mg daily for 6 months. The primary endpoint was durable response at the 6-month follow-up. A total of 35 patients were enrolled. Durable response was achieved in 20 patients (57.1%, 95% confidence interval, 39.9 to 74.4), and initial response in 23 (65.7%) patients. For patients responding to baricitinib, the median time to response was 12 (IQR 6-20) days, and the median peak platelet count was 94 (IQR 72-128) × 109/L. Among the 27 patients undergoing extend observation, 12 (44.4%) remained responsive for a median duration of approximately 20 weeks after baricitinib discontinuation. Adverse events were reported in 11 (31.4%) patients, including infections in 6 (17.1%) patients during the treatment period. Treatment discontinuation due to an adverse event was reported in 2 (5.7%) patients. Evidence from this pilot study suggested that baricitinib might be a novel candidate for the armamentarium of ITP-modifying agents. Future studies are warranted to validate the safety, efficacy, and optimal dosing of baricitinib in patients with ITP.

Silica nanoparticle design for colorectal cancer treatment: Recent progress and clinical potential.

Colorectal cancer (CRC) is the third most common cancer worldwide and the second most common cause of cancer death. Nanotherapies are able to selectively target the delivery of cancer therapeutics, thus improving overall antitumor efficiency and reducing conventional chemotherapy side effects. Mesoporous silica nanoparticles (MSNs) have attracted the attention of many researchers due to their remarkable advantages and biosafety. We offer insights into the recent advances of MSNs in CRC treatment and their potential clinical application value.

Asymmetric Synthesis and Biological Evaluation of Platensilin, Platensimycin, Platencin, and Their Analogs via a Bioinspired Skeletal Reconstruction Approach.

Platensilin, platensimycin, and platencin are potent inhibitors of ß-ketoacyl-acyl carrier protein synthase (FabF) in the bacterial and mammalian fatty acid synthesis system, presenting promising drug leads for both antibacterial and antidiabetic therapies. Herein, a bioinspired skeleton reconstruction approach is reported, which enables the unified synthesis of these three natural FabF inhibitors and their skeletally diverse analogs, all stemming from a common ent-pimarane core. The synthesis features a diastereoselective biocatalytic reduction and an intermolecular Diels-Alder reaction to prepare the common ent-pimarane core. From this intermediate, stereoselective Mn-catalyzed hydrogen atom-transfer hydrogenation and subsequent Cu-catalyzed carbenoid C-H insertion afford platensilin. Furthermore, the intramolecular Diels-Alder reaction succeeded by regioselective ring opening of the newly formed cyclopropane enables the construction of the bicyclo[3.2.1]-octane and bicyclo[2.2.2]-octane ring systems of platensimycin and platencin, respectively. This skeletal reconstruction approach of the ent-pimarane core facilitates the preparation of analogs bearing different polycyclic scaffolds. Among these analogs, the previously unexplored cyclopropyl analog 47 exhibits improved antibacterial activity (MIC80 = 0.0625 µg/mL) against S. aureus compared to platensimycin.

Clinical characteristics of membranous nephropathy after allogeneic hematopoietic stem cell transplantation: A real-world multicenter study.

Membranous nephropathy (MN) is a rare complication that can occur after allogeneic hematopoietic stem cell transplantation (allo-HSCT). MN patients may develop nephrotic syndrome or even kidney failure, which greatly affects their quality of life and prognosis. However, current knowledge regarding MN after allo-HSCT is limited. Thus, a multicenter nested case‒control study was conducted. Patients who had been diagnosed with MN after allo-HSCT were retrospectively identified at 8 HSCT centers. A total of 51 patients with MN after allo-HSCT were included. The median age of MN patients after allo-HSCT was 38 years, and the median duration from HSCT to MN was 18 months. The use of HLA-matched donors (P = 0.0102) and peripheral blood as the graft source (P = 0.0060) were identified as independent predisposing risk factors for the onset of MN after allo-HSCT. Compared to those in the control group, the incidence of extensive chronic graft-versus-host disease was greater in the MN patients (P = 0.0002). A total of 31 patients developed nephrotic syndrome. Patients receiving combination treatments of corticosteroids and immunosuppressants appeared to have better outcomes. In conclusion, MN is a rare but occasionally severe complication following HSCT and may require active treatment.

Comparative efficacy and safety of Chinese patent medicines of iron deficiency anemia during pregnancy: A network meta-analysis.

BACKGROUND: Iron deficiency anemia (IDA) is a prevalent nutritional disorder during pregnancy. Clinical studies indicate that incorporating Chinese patent medicines (CPMs) with oral iron (OI) in treating IDA in pregnancy can reduce adverse effects and improve clinical outcomes. Nonetheless, the comparative efficacy of different CPMs remains unclear. AIM: To assess the safety and effectiveness of different CPMs for treating IDA during pregnancy using network meta-analysis. METHODS: We conducted a search for randomized controlled trials (RCTs) that combined CPM and OI for IDA treatment in pregnancy, spanning from 2013 to the present. Data analysis was performed using Rev Man 5.3 and Stata 14.0 on literature that satisfied the quality criteria. RESULTS: The analysis included 45 RCTs, encompassing 4422 pregnant patients with IDA. Six CPMs were examined, including Shengxuebao Mixture, Shengxuening Tablets (SXN), Yiqi Weixue CPMs (YQWX), Jianpi Shengxue CPMs (JPSX), Yiqi Buxue Tablets, and Compound Hongyi Buxue Oral Liquid (FFHY). Findings indicated that FFHY + OI significantly improved the clinical effective rate. SXN + OI was most effective in boosting red blood cells counts and hemoglobin levels. YQWX + OI showed superior results in improving serum ferritin, and SXN + OI was most effective in increasing serum iron levels. JPSX + OI was optimal in reducing adverse pregnancy outcomes, while YQBX + OI effectively minimized adverse events. A cluster analysis suggested that SXN + OI could be the potentially optimal therapeutic regimen for IDA in pregnancy. CONCLUSION: This study demonstrates that the combination of OI with CPMs offers better outcomes than OI alone. Based on clinical efficacy and other measured outcomes, SXN + OI emerges as the most effective treatment modality for improving the health of pregnant patients with IDA.

Functionality of arbuscular mycorrhizal fungi varies across different growth stages of maize under drought conditions.

Physio-biochemical regulations governing crop growth period are pivotal for drought adaptation. Yet, the extent to which functionality of arbuscular mycorrhizal fungi (AM fungi) varies across different stages of maize growth under drought conditions remains uncertain. Therefore, periodic functionality of two different AM fungi i.e., Rhizophagus irregularis SUN16 and Glomus monosporum WUM11 were assessed at jointing, silking, and pre-harvest stages of maize subjected to different soil moisture gradients i.e., well-watered (80% SMC (soil moisture contents)), moderate drought (60% SMC), and severe drought (40% SMC). The study found that AM fungi significantly (p < 0.05) affected various morpho-physiological and biochemical parameters at different growth stages of maize under drought. As the plants matured, AM fungi enhanced root colonization, glomalin contents, and microbial biomass, leading to increased nutrient uptake and antioxidant activity. This boosted AM fungal activity ultimately improved photosynthetic efficiency, evident in increased photosynthetic pigments and photosynthesis. Notably, R. irregularis and G. monosporum improved water use efficiency and mycorrhizal dependency at critical growth stages like silking and pre-harvest, indicating their potential for drought resilience to stabilize yield. The principal component analysis highlighted distinct plant responses to drought across growth stages and AM fungi, emphasizing the importance of early-stage sensitivity. These findings underscore the potential of incorporating AM fungi into agricultural management practices to enhance physiological and biochemical responses, ultimately improving drought tolerance and yield in dryland maize cultivation.

YTHDF2 regulates MSS51 expression contributing to mitochondria dysfunction of granulosa cells in polycystic ovarian syndrome patients.

RESEARCH QUESTION: Granulosa cells (GCs) dysfunction plays a crucial role in the pathogenesis of polycystic ovary syndrome (PCOS). It is reported that YTH domain-containing family protein 2 (YTHDF2) is upregulated in mural GCs of PCOS patients. What effect does the differential expression of YTHDF2 have in PCOS patients? DESIGN: Mural GCs and cumulus GCs from 15 patients with PCOS and 15 ovulatory controls and 4 cases of pathological sections in each group were collected. Real-time PCR, Western Blot, immunohistochemistry, and immunofluorescence experiments were conducted to detect gene and protein expression. RNA immunoprecipitation assay was performed to evaluate the binding relationship between YTHDF2 and MSS51. Mitochondrial morphology, cellular ATP and ROS levels and glycolysis-related gene expression were detected after YTHDF2 overexpression or MSS51 inhibition. RESULTS: In the present study, we found that YTHDF2 was upregulated in GCs of PCOS patients while MSS51 was downregulated. YTHDF2 protein can bind to MSS51 mRNA and affect MSS51 expression. The reduction of MSS51 expression or the increase in YTHDF2 expression can lead to mitochondrial damage, reduced ATP levels, increased ROS levels and reduced expression of LDHA, PFKP and PKM. CONCLUSIONS: YTHDF2 may regulate the expression of MSS51, affecting the structure and function of mitochondria in GCs and interfering with cellular glycolysis, which may disturb the normal biological processes of GCs and follicle development in PCOS patients.

Multi-gene phylogenetic and taxonomic contributions to Xylaria (Ascomycota) associated with fallen fruits from China.

Morphological and phylogenetic analyses on samples of Xylaria species associated with fallen fruits from China were carried out, and two new species were described, namely X.aleuriticola and X.microcarpa. Xylariaaleuriticola is found on fallen fruits of Aleuritesmoluccana, and characterized by stromata dichotomously branched several times with long acute sterile apices, fertile parts roughened with perithecia and tomentose, and ellipsoid to fusiform ascospores. Xylariamicrocarpa differs in its very small stromata with dark brown tomentum, light brown ascospores with an inconspicuous straight germ slit, and grows on leguminous pods. The differences between the new species and morphologically similar species are discussed. Phylogenetic analyses on ITS-RPB2-TUB sequences confirmed that the two species are clearly separated from other species of the genus Xylaria. Xylarialiquidambaris is reported as a new record from China. A key to the Xylaria species associated with fallen fruits and seeds reported from China is provided to facilitate future studies of the genus.

Prediction of miRNAs and diseases association based on sparse autoencoder and MLP.

Introduction: MicroRNAs (miRNAs) are small and non-coding RNA molecules which have multiple important regulatory roles within cells. With the deepening research on miRNAs, more and more researches show that the abnormal expression of miRNAs is closely related to various diseases. The relationship between miRNAs and diseases is crucial for discovering the pathogenesis of diseases and exploring new treatment methods. Methods: Therefore, we propose a new sparse autoencoder and MLP method (SPALP) to predict the association between miRNAs and diseases. In this study, we adopt advanced deep learning technologies, including sparse autoencoder and multi-layer perceptron (MLP), to improve the accuracy of predicting miRNA-disease associations. Firstly, the SPALP model uses a sparse autoencoder to perform feature learning and extract the initial features of miRNAs and diseases separately, obtaining the latent features of miRNAs and diseases. Then, the latent features combine miRNAs functional similarity data with diseases semantic similarity data to construct comprehensive miRNAs-diseases datasets. Subsequently, the MLP model can predict the unknown association among miRNAs and diseases. Result: To verify the performance of our model, we set up several comparative experiments. The experimental results show that, compared with traditional methods and other deep learning prediction methods, our method has significantly improved the accuracy of predicting miRNAs-disease associations, with 94.61% accuracy and 0.9859 AUC value. Finally, we conducted case study of SPALP model. We predicted the top 30 miRNAs that might be related to Lupus Erythematosus, Ecute Myeloid Leukemia, Cardiovascular, Stroke, Diabetes Mellitus five elderly diseases and validated that 27, 29, 29, 30, and 30 of the top 30 are indeed associated. Discussion: The SPALP approach introduced in this study is adept at forecasting the links between miRNAs and diseases, addressing the complexities of analyzing extensive bioinformatics datasets and enriching the comprehension contribution to disease progression of miRNAs.

A new prediction model for acute kidney injury following liver transplantation using grafts from donors after cardiac death.

Acute kidney injury (AKI) is a major complication following liver transplantation (LT), which utilizes grafts from donors after cardiac death (DCD). We developed a machine-learning-based model to predict AKI, using data from 894 LT recipients (January 2015-March 2021), split into training and testing sets. Five machine learning algorithms were employed to construct the prediction models using 17 clinical variables. The performance of the models was assessed by the area under the receiver operating characteristic curve (AUC), accuracy, F1-score, sensitivity and specificity. The best-performing model was further validated in an independent cohort of 195 LT recipients who received DCD grafts between April 2021 and December 2021. The Shapley additive explanations method was utilized to elucidate the predictions and identify the most crucial features. The gradient boosting machine (GBM) model demonstrated the highest AUC (0.76, 95% CI: 0.70-0.82), F1-score (0.73, 95% CI: 0.66-0.79) and sensitivity (0.74, 95% CI: 0.66-0.80) in the testing set and a comparable AUC (0.75, 95% CI: 0.67-0.81) in the validation set. The GBM model identified high preoperative indirect bilirubin, low intraoperative urine output, prolonged anesthesia duration, low preoperative platelet count and graft steatosis graded NASH Clinical Research Network 1 and above as the top five important features for predicting AKI following LT using DCD grafts. The GBM model is a reliable and interpretable tool for predicting AKI in recipients of LT using DCD grafts. This model can assist clinicians in identifying patients at high risk and providing timely interventions to prevent or mitigate AKI.

Improved Intrusion Detection Based on Hybrid Deep Learning Models and Federated Learning.

The security of the Industrial Internet of Things (IIoT) is of vital importance, and the Network Intrusion Detection System (NIDS) plays an indispensable role in this. Although there is an increasing number of studies on the use of deep learning technology to achieve network intrusion detection, the limited local data of the device may lead to poor model performance because deep learning requires large-scale datasets for training. Some solutions propose to centralize the local datasets of devices for deep learning training, but this may involve user privacy issues. To address these challenges, this study proposes a novel federated learning (FL)-based approach aimed at improving the accuracy of network intrusion detection while ensuring data privacy protection. This research combines convolutional neural networks with attention mechanisms to develop a new deep learning intrusion detection model specifically designed for the IIoT. Additionally, variational autoencoders are incorporated to enhance data privacy protection. Furthermore, an FL framework enables multiple IIoT clients to jointly train a shared intrusion detection model without sharing their raw data. This strategy significantly improves the model's detection capability while effectively addressing data privacy and security issues. To validate the effectiveness of the proposed method, a series of experiments were conducted on a real-world Internet of Things (IoT) network intrusion dataset. The experimental results demonstrate that our model and FL approach significantly improve key performance metrics such as detection accuracy, precision, and false-positive rate (FPR) compared to traditional local training methods and existing models.

Ethereum Phishing Scam Detection Based on Data Augmentation Method and Hybrid Graph Neural Network Model.

The rapid advancement of blockchain technology has fueled the prosperity of the cryptocurrency market. Unfortunately, it has also facilitated certain criminal activities, particularly the increasing issue of phishing scams on blockchain platforms such as Ethereum. Consequently, developing an efficient phishing detection system is critical for ensuring the security and reliability of cryptocurrency transactions. However, existing methods have shortcomings in dealing with sample imbalance and effective feature extraction. To address these issues, this study proposes an Ethereum phishing scam detection method based on DA-HGNN (Data Augmentation Method and Hybrid Graph Neural Network Model), validated by real Ethereum datasets to prove its effectiveness. Initially, basic node features consisting of 11 attributes were designed. This study applied a sliding window sampling method based on node transactions for data augmentation. Since phishing nodes often initiate numerous transactions, the augmented samples tended to balance. Subsequently, the Temporal Features Extraction Module employed Conv1D (One-Dimensional Convolutional neural network) and GRU-MHA (GRU-Multi-Head Attention) models to uncover intrinsic relationships between features from the time sequences and to mine adequate local features, culminating in the extraction of temporal features. The GAE (Graph Autoencoder) concept was then leveraged, with SAGEConv (Graph SAGE Convolution) as the encoder. In the SAGEConv reconstruction module, by reconstructing the relationships between transaction graph nodes, the structural features of the nodes were learned, obtaining reconstructed node embedding representations. Ultimately, phishing fraud nodes were further identified by integrating temporal features, basic features, and embedding representations. A real Ethereum dataset was collected for evaluation, and the DA-HGNN model achieved an AUC-ROC (Area Under the Receiver Operating Characteristic Curve) of 0.994, a Recall of 0.995, and an F1-score of 0.994, outperforming existing methods and baseline models.

Root-to-shoot signaling positively mediates source-sink relation in late growth stages in diploid and tetraploid wheat.

Non-hydraulic root source signaling (nHRS) is a unique positive response to soil drying in the regulation of plant growth and development. However, it is unclear how the nHRS mediates the tradeoff between source and sink at the late growth stages and its adaptive mechanisms in primitive wheat. To address this issue, a root-splitting design was made by inserting solid partition in the middle of the pot culture to induce the occurrence of nHRS using four wheat cultivars (MO1 and MO4, diploid; DM22 and DM31, tetraploid) as materials. Three water treatments were designed as 1) both halves watered (CK), 2) holistic root system watered then droughted (FS), 3) one-half of the root system watered and half droughted (PS). FS and PS were designed to compare the role of the full root system and split root system to induce nHRS. Leaves samples were collected during booting and anthesis to compare the role of nHRS at both growth stages. The data indicated that under PS treatment, ABA concentration was significantly higher than FS and CK, demonstrating the induction of nHRS in split root design and nHRS decreased cytokinin (ZR) levels, particularly in the PS treatment. Soluble sugar and proline accumulation were higher in the anthesis stage as compared to the booting stage. POD activity was higher at anthesis, while CAT was higher at the booting stage. Increased ABA (nHRS) correlated with source-sink relationships and metabolic rate (i.e., leaf) connecting other stress signals. Biomass density showed superior resource acquisition and utilization capabilities in both FS and PS treatment as compared to CK in all plants. Our findings indicate that nHRS-induced alterations in phytohormones and their effect on source-sink relations were allied with the growth stages in primitive wheat.

Genomic characterization reveals distinct mutational landscapes and therapeutic implications between different molecular subtypes of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) has high heterogeneity, poor prognosis, and limited treatment success. Recently, an immunohistochemistry-based surrogate classification for the "Fudan University Shanghai Cancer Center (FUSCC) subtyping" has been developed and is considered more suitable for clinical application. Seventy-one paraffin-embedded sections of surgically resected TNBC were classified into four molecular subtypes using the IHC-based surrogate classification. Genomic analysis was performed by targeted next-generation sequencing and the specificity of the subtypes was explored by bioinformatics, including survival analysis, multivariate Cox regression, pathway enrichment, Pyclone analysis, mutational signature analysis and PHIAL analysis. AKT1 and BRCA1 mutations were identified as independent prognostic factors in TNBC. TNBC molecular subtypes encompass distinct genomic landscapes that show specific heterogeneities. The luminal androgen receptor (LAR) subtype was associated with mutations in PIK3CA and PI3K pathways, which are potentially sensitive to PI3K pathway inhibitors. The basal-like immune-suppressed (BLIS) subtype was characterized by high genomic instability and the specific possession of signature 19 while patients in the immunomodulatory (IM) subtype belonged to the PD-L1 ≥ 1% subgroup with enrichment in Notch signaling, suggesting a possible benefit of immune checkpoint inhibitors and Notch inhibitors. Moreover, mesenchymal-like (MES) tumors displayed enrichment in the receptor tyrosine kinase (RTK)-RAS pathway and potential sensitivity to RTK pathway inhibitors. The findings suggest potential treatment targets and prognostic factors, indicating the possibility of TNBC stratified therapy in the future.

Genomic analysis of Cobetia sp. D5 reveals its role in marine sulfur cycling.

Dimethylsulfoniopropionate (DMSP) is one of the most abundant sulfur-containing organic compounds on the earth, which is an important carbon and sulfur source and plays an important role in the global sulfur cycle. Marine microorganisms are an important group involved in DMSP metabolism. The strain Cobetia sp. D5 was isolated from seawater samples in the Yellow Sea area of Qingdao during an algal bloom. There is still limited knowledge on the capacity of DMSP utilization of Cobetia bacteria. The study reports the whole genome sequence of Cobetia sp. D5 to understand its DMSP metabolism pathway. The genome of Cobetia sp. D5 consists of a circular chromosome with a length of 4,233,985 bp and the GC content is 62.56%. Genomic analysis showed that Cobetia sp. D5 contains a set of genes to transport and metabolize DMSP, which can cleave DMSP to produce dimethyl sulphide (DMS) and 3-Hydroxypropionyl-Coenzyme A (3-HP-CoA). DMS diffuses into the environment to enter the global sulfur cycle, whereas 3-HP-CoA is catabolized to acetyl CoA to enter central carbon metabolism. Thus, this study provides genetic insights into the DMSP metabolic processes of Cobetia sp. D5 during a marine algal bloom, and contributes to the understanding of the important role played by marine bacteria in the global sulfur cycle.

Association Between Preeclampsia and Blood Pressure in Offspring: A Systematic Review and Meta-Analysis.

PURPOSE OF REVIEW: Pregnancy-induced preeclampsia is a severe pregnancy complication and preeclampsia has been associated with an increased risk of chronic hypertension for offspring. However, the magnitude of the overall effect of exposure to preeclampsia in pregnancy on blood pressure (BP) in offspring is unknown. This systematic review and meta-analysis was sought to systematically assess the effects of preeclampsia on the BP of the offspring. RECENT FINDINGS: Of 2550 publications identified, 23 studies were included. The meta-analysis indicated that preeclampsia increases the potential risk of hypertension in offspring. Systolic blood pressure (SBP) was 2.0 mm Hg (95% CI: 1.2, 2.8) and diastolic blood pressure (DBP) was 1.4 mm Hg (95% CI: 0.9, 1.9) higher in offspring exposed to pre-eclampsia in utero, compared to those born to normotensive mothers. The correlations were similar in stratified analyses of children and adolescents by sex, geographic area, ages, and gestational age. During childhood and young adulthood, the offspring of pregnant women with preeclampsia are at an increased risk of high BP. It is crucial to monitor their BP.

Antiviral C-geranylated flavonoids from Artocarpus communis.

Ten C-geranylated flavonoids, along with three known analogues, were isolated from the leaves of Artocarpus communis. The chemical structures of these compounds were unambiguously determined via comprehensive spectroscopic analysis, single-crystal X-ray diffraction experiments, and quantum chemical electronic circular dichroism calculations. Structurally, artocarones A-I (1-9) represent a group of unusual, highly modified C-geranylated flavonoids, in which the geranyl chain is cyclised with the ortho-hydroxy group of flavonoids to form various heterocyclic scaffolds. Notably, artocarones E and G-I (5 and 7-9) feature a 6H-benzo[c]chromene core that is hitherto undescribed in C-geranylated flavonoids. Artocarone J (10) is the first example of C-9-C-16 connected C-geranylated aurone. Meanwhile, the plausible biosynthetic pathways for these rare C-geranylated flavonoids were also proposed. Notably, compounds 1, 2, 4, 8, 11, and 12 exhibited promising in vitro inhibitory activities against respiratory syncytial virus and herpes simplex virus type 1.